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There are many ways to record execution time. You could use a simple stopwatch and record the time based on observation or you could add code that captures the system time. This latter method is perhaps the quickest and most reliable way to determine relative speed. I use the term relative because many factors concerning the environment and what is running at the time of the execution could affect performance. When you conduct your test runs, be sure to use multiple test runs and perform statistical analysis on the results. This will give you a normalized set of data to compare.

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Figure 5.1 In the conventional logging solution, all log points must issue calls to the logger explicitly.

Question 4. Why is the remove duplicates operation not necessary for the intersect operation Are there any conditions where this is false If so, what are they

In both outline (Report) layout and Crosstab (tabular) layout, you can format an outer row field so each item has a blank row after it: 1. Double-click the field button to open the PivotTable Field dialog box. 2. Click the Layout button. 3. Add a checkmark to Insert blank line after each item. 4. Click OK, then click OK to close the PivotTable Field dialog box.

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As you can see, the logging calls will be all over the core modules. When a new module is added to the system, all of its methods that need logging must be instrumented. Such instrumentation is invasive, causing the tangling of the core concerns with the logging concern. Further, if you ever happen to change the logging toolkit to a different API, you need to revisit every logging statement and modify it. Consistency is the single most important requirement of logging. It means that if the logging specification requires that certain kinds of operations be logged, then the implementation must log every invocation of those operations. When things go wrong in a system, doubting the logging consistency is probably the last thing you want to do. Missed logging calls can make output hard to understand and sometimes useless. Achieving consistency using conventional logging is a lofty goal, and while systems can attain it initially, it requires continuing vigilance to keep it so. For example, if you add new classes to the system or new methods in existing classes, you must ensure that they implement logging that matches the current logging strategy.

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Let s consider what an intersect operation is. It is simply the rows that appear in each of the tables involved (you can intersect on more than two tables). Duplicates in this case are not possible if the tables themselves do not have duplicates. However, if the tables are the result of operations performed in the tree below and have not had the duplicates removed and the distinct operation is included in the query, you will need to remove duplicates. Basically, this is an it depends answer.

You can t enter text in the blank row, but you can format the row for example, add a fill color to Tip

Although logging APIs solve quite a few problems, as you have just seen they also leave some gaps The limitations are not a result of the logging APIs or their implementations; rather, they stem from the fundamental limitations of objectoriented programming, which require embedding the logging invocations in each module AOP and AspectJ overcome those limitations AspectJ easily implements the invocation of logging statements from all the log points The beauty is that you do not need to actually instrument any log points; writing an aspect does it automatically Further, since there is a central place to control logging operations, you achieve consistency easily The most fundamental difference between conventional logging and AspectJbased logging is modularization of the logging concern.

Question 5. (advanced) MySQL does not currently support a cross-product or intersect operation (as defined by Date). Change the MySQL parser to recognize these new keywords and process queries like SELECT * FROM A CROSS B and SELECT * FROM A INTERSECT B and add these functions to the execution engine. Hint: See the do_join() method.

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